Title :
Tracking Objects with Adaptive Feature Patches for PTZ Camera Visual Surveillance
Author :
Xie, Yi ; Lin, Liang ; Jia, Yunde
Author_Institution :
Beijing Lab. of Intell. Inf., Beijing Inst. of Technol., Beijing, China
Abstract :
Compared to the traditional tracking with fixed cameras, the PTZ-camera-based tracking is more challenging due to (i) lacking of reliable background modeling and subtraction; (ii) the appearance and scale of target changing suddenly and drastically. Tackling these problems, this paper proposes a novel tracking algorithm using patch-based object models and demonstrates its advantages with the PTZ-camera in the application of visual surveillance. In our method, the target model is learned and represented by a set of feature patches whose discriminative power is higher than others. The target model is matched and evaluated by both appearance and motion consistency measurements. The homography between frames is also calculated for scale adaptation. The experiment on several surveillance videos shows that our method outperforms the state-of-arts approaches.
Keywords :
image matching; image motion analysis; object detection; target tracking; video cameras; video surveillance; PTZ camera visual surveillance; PTZ-camera-based tracking; adaptive feature patches; motion consistency measurements; object tracking algorithm; patch-based object models; video surveillance; Adaptation model; Cameras; Surveillance; Target tracking; Videos; Visualization; PTZ based tracking; feature pursuit; patch based object models;
Conference_Titel :
Pattern Recognition (ICPR), 2010 20th International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-1-4244-7542-1
DOI :
10.1109/ICPR.2010.430